{"id":50752,"date":"2021-04-20T00:00:00","date_gmt":"2021-04-20T07:00:00","guid":{"rendered":"https:\/\/griddb-linux-hte8hndjf8cka8ht.westus-01.azurewebsites.net\/%e6%9c%aa%e5%88%86%e9%a1%9e\/using-geographical-queries-based-on-bounding-boxes\/"},"modified":"2025-11-14T07:54:45","modified_gmt":"2025-11-14T15:54:45","slug":"using-geographical-queries-based-on-bounding-boxes","status":"publish","type":"post","link":"https:\/\/www.griddb.net\/ja\/%e6%9c%aa%e5%88%86%e9%a1%9e\/using-geographical-queries-based-on-bounding-boxes\/","title":{"rendered":"\u30d0\u30a6\u30f3\u30c7\u30a3\u30f3\u30b0\u30dc\u30c3\u30af\u30b9\u3067\u5730\u7406\u7684\u30af\u30a8\u30ea\u3092\u4f7f\u3046"},"content":{"rendered":"<p>\u4ee5\u524d\u306e<a href=\"https:\/\/griddb.net\/en\/blog\/geospatial-analysis-of-nyc-crime-data-with-griddb\/\">\u30cb\u30e5\u30fc\u30e8\u30fc\u30af\u306e\u72af\u7f6a\u306b\u95a2\u3059\u308b\u30d6\u30ed\u30b0<\/a>\u3067\u306f\u3001GridDB\u306e\u30b8\u30aa\u30e1\u30c8\u30ea\uff08\u5e7e\u4f55\u5b66\uff09\u6a5f\u80fd\u3092\u4f7f\u3063\u305f\u5730\u7406\u7a7a\u9593\u30c7\u30fc\u30bf\u306e\u30af\u30a8\u30ea\u306b\u3064\u3044\u3066\u7d39\u4ecb\u3057\u307e\u3057\u305f\u3002<\/p>\n<p>\u30b8\u30aa\u30e1\u30c8\u30ea\u3068WKT\uff08\u3088\u304f\u77e5\u3089\u308c\u3066\u3044\u308b\u5e7e\u4f55\u5b66\u306e\u30c6\u30ad\u30b9\u30c8\u8868\u73fe\uff09\u306e\u30af\u30a8\u30ea\u306f\u3046\u307e\u304f\u6a5f\u80fd\u3057\u307e\u3059\u304c\u3001\u6570\u5024\u6bd4\u8f03\u3088\u308a\u3082\u8a08\u7b97\u91cf\u304c\u591a\u3044\u3053\u3068\u3001C\u3068Java\u306eAPI\u3067\u3057\u304b\u5229\u7528\u3067\u304d\u306a\u3044\u3053\u3068\u3001\u3068\u3044\u30462\u3064\u306e\u6b20\u70b9\u304c\u3042\u308a\u307e\u3059\u3002Python\u3084JDBC\u3092\u4f7f\u3044\u305f\u3044\u5834\u5408\u306f\u3001\u5225\u306e\u65b9\u6cd5\u3092\u4f7f\u3046\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u3053\u306e\u30d6\u30ed\u30b0\u3067\u306f\u3001\u540c\u3058\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306b\u5358\u7d14\u306a\u30d0\u30a6\u30f3\u30c7\u30a3\u30f3\u30b0\u30dc\u30c3\u30af\u30b9\u3092\u4f7f\u3063\u305f\u30af\u30a8\u30ea\u3092\u7d39\u4ecb\u3057\u307e\u3059\u3002\u307e\u305f\u3001\u5730\u7406\u7a7a\u9593\u30c7\u30fc\u30bf\u3092\u8907\u6570\u306e\u30b3\u30f3\u30c6\u30ca\u306b\u5206\u5272\u3059\u308b\u65b9\u6cd5\u306b\u3064\u3044\u3066\u3082\u7d39\u4ecb\u3057\u307e\u3059\u3002<\/p>\n<h2>\u30d1\u30fc\u30c6\u30a3\u30b7\u30e7\u30f3\u30c7\u30fc\u30bf<\/h2>\n<p>GridDB\u306e\u30ad\u30fc\u30b3\u30f3\u30c6\u30ca\u30a2\u30fc\u30ad\u30c6\u30af\u30c1\u30e3\u3092\u5229\u7528\u3059\u308b\u305f\u3081\u306b\u3001\u30c7\u30fc\u30bf\u3092\u7570\u306a\u308b\u30b3\u30f3\u30c6\u30ca\u306b\u5206\u5272\u3057\u307e\u3059\u3002\u3053\u308c\u306b\u3088\u308a\u3001\u30c7\u30fc\u30bf\u3092\u5747\u7b49\u306b\u5206\u6563\u3055\u305b\u306a\u304c\u3089\u3001\u30d0\u30a4\u30ca\u30ea\u691c\u7d22\u30c4\u30ea\u30fc\u3092\u975e\u5e38\u306b\u77ed\u304f\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n<p>\u3053\u308c\u306b\u306f\u3044\u304f\u3064\u304b\u306e\u65b9\u6cd5\u304c\u3042\u308a\u307e\u3059\u304c\u3001\u4eca\u56de\u306f\u6700\u3082\u30b7\u30f3\u30d7\u30eb\u306a\u3001\u7def\u5ea6\u3068\u7d4c\u5ea6\u3092\u56db\u6368\u4e94\u5165\u3059\u308b\u65b9\u6cd5\u3092\u7d39\u4ecb\u3057\u307e\u3059\u3002<\/p>\n<p>Java\u3067\u306fDecimalFormat\u3067\u5b9f\u73fe\u3057\u3066\u3044\u307e\u3059\u304c\u3001Python\u3067\u306fmath.ceil()\u3068if\u3092\u4f7f\u3063\u3066\u3044\u307e\u3059\u3002<\/p>\n<div class=\"clipboard\">\n<pre><code class=\"language-java\">DecimalFormat df = new DecimalFormat(\"#\");\ndf.setRoundingMode(RoundingMode.CEILING);\ndf.setNegativePrefix(\"n\");\nString cName = \"geo_\"+df.format(c.Latitude*100)+\"_\"+df.format(c.Longitude*100);\n<\/code><\/pre>\n<\/div>\n<div class=\"clipboard\">\n<pre><code class=\"language-py\">cname = \"geo_\"+re.sub('-','n', str(math.ceil(lat*100)))+\"_\"+re.sub('-','n',str(math.ceil(lon*100)))))\n<\/code><\/pre>\n<\/div>\n<p>\u6700\u521d\u306e\u30d6\u30ed\u30b0\u3067\u7d39\u4ecb\u3057\u305fIngest.java\u3092\u4fee\u6b63\u3057\u3001\u30b8\u30aa\u30e1\u30c8\u30ea\u30c7\u30fc\u30bf\u30bf\u30a4\u30d7\u3092\u4f7f\u3063\u3066\u30c7\u30fc\u30bf\u3092\u7167\u4f1a\u3057\u307e\u3057\u305f\u3002<\/p>\n<div class=\"clipboard\">\n<pre><code class=\"language-py\">DecimalFormat df = new DecimalFormat(\"#\");\ndf.setRoundingMode(RoundingMode.CEILING);\ndf.setNegativePrefix(\"n\");\nfor (CSVRecord record : records) {\n    try {\n        if (i++ % 1000 == 0) System.out.println(\"Ingesting \"+ i);\n        Complaint c = parseCsvRecord(record);\n        if(c != null) {\n            String cName = \"geo_\"+df.format(c.Latitude*100)+\"_\"+df.format(c.Longitude*100);\n            System.out.println(\"adding \"+c+\" to \"+cName); \n            Collection&lt;String, Complaint> col = store.putCollection(cName, Complaint.class);\n            col.setAutoCommit(false);\n            col.put(c);\n            col.commit();\n        }\n    } catch(Exception e) {\n        System.out.println(\"Failed to ingest \"+i);\n        System.out.println(e);\n    }\n}\n\n<\/code><\/pre>\n<\/div>\n<p>\u3053\u308c\u306b\u3088\u308a\u3001\u4ee5\u4e0b\u306e\u51fa\u529b\u304c\u5f97\u3089\u308c\u307e\u3059\u3002<\/p>\n<div class=\"clipboard\">\n<pre><code class=\"language-bash\">adding 927207428: Fri Jan 03 13:30:00 GMT 2014 @ (40.745241809, -73.894253382) to geo_4075_n7389\nadding 492142357: Wed Apr 13 00:00:00 BST 2016 @ (40.810351863, -73.924942326) to geo_4082_n7392\nadding 572616350: Mon Aug 18 14:30:00 BST 2014 @ (40.683659778, -73.85154207) to geo_4069_n7385\n... snip ...\n<\/code><\/pre>\n<\/div>\n<h2>\u30d0\u30a6\u30f3\u30c7\u30a3\u30f3\u30b0\u30dc\u30c3\u30af\u30b9<\/h2>\n<p>GridDB\u306b\u30c7\u30fc\u30bf\u304c\u4fdd\u5b58\u3055\u308c\u305f\u306e\u3067\u3001\u7167\u4f1a\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u308b\u3088\u3046\u306b\u306a\u308a\u307e\u3057\u305f\u3002\u307e\u305a\u306f\u3001\u5883\u754c\u3092\u898b\u3064\u3051\u3066\u307f\u307e\u3057\u3087\u3046\u3002Python\u3067\u306f\u3001geopy distance\u30e2\u30b8\u30e5\u30fc\u30eb\u3092\u4f7f\u3046\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n<div class=\"clipboard\">\n<pre><code class=\"language-py\">import geopy\nfrom geopy import distance\n\nd = geopy.distance.geodesic(meters=radius)\nstart = geopy.Point(lat, lon)\n\nnorth = d.destination(point=start, bearing=0)[0]\nsouth = d.destination(point=start, bearing=180)[0]\neast = d.destination(point=start, bearing=90)[1]\nwest = d.destination(point=start, bearing=270)[1]\n<\/code><\/pre>\n<\/div>\n<p>\u30c7\u30fc\u30bf\u304c\u5206\u5272\u3055\u308c\u3066\u3044\u308b\u306e\u3067\u3001\u6b21\u306e\u30b9\u30c6\u30c3\u30d7\u3067\u306f\u3001\u30af\u30a8\u30ea\u304c\u5fc5\u8981\u3068\u306a\u308b\u53ef\u80fd\u6027\u306e\u3042\u308b\u30b3\u30f3\u30c6\u30ca\u306e\u30ea\u30b9\u30c8\u3092\u751f\u6210\u3057\u307e\u3059\u3002<\/p>\n<p>\u30af\u30a8\u30ea\u30a8\u30ea\u30a2\u306e\u8ddd\u96e2\u304c\u30d1\u30fc\u30c6\u30a3\u30b7\u30e7\u30f3\u30b5\u30a4\u30ba\u3088\u308a\u3082\u5c0f\u3055\u3044\u5834\u5408\u306f\u3001\u30b3\u30f3\u30c6\u30ca\u30921\u3064\u306e\u30bb\u30c3\u30c8\u3068\u3057\u3066\u5b9a\u7fa9\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n<div class=\"clipboard\">\n<pre><code class=\"language-py\">containers = {  re.sub('-', 'n', re.sub('.', '', \"geo_%d_%d\" %(math.ceil(north*100), math.ceil(east*100)))),\n                re.sub('-', 'n', re.sub('.', '', \"geo_%d_%d\" %(math.ceil(north*100), math.ceil(west*100)))),\n                re.sub('-', 'n', re.sub('.', '', \"geo_%d_%d\" %(math.ceil(south*100), math.ceil(east*100)))),\n                re.sub('-', 'n', re.sub('.', '', \"geo_%d_%d\" %(math.ceil(south*100), math.ceil(west*100))))};\n\n<\/code><\/pre>\n<\/div>\n<p>\u3057\u304b\u3057\u3001\u30af\u30a8\u30ea\u9818\u57df\u304c\u30d1\u30fc\u30c6\u30a3\u30b7\u30e7\u30f3\u30b5\u30a4\u30ba\u3088\u308a\u3082\u5927\u304d\u3044\u5834\u5408\u306f\u3001\u53ef\u80fd\u306a\u3059\u3079\u3066\u306e\u30b3\u30f3\u30c6\u30ca\u3092\u7e70\u308a\u8fd4\u3057\u51e6\u7406\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n<div class=\"clipboard\">\n<pre><code class=\"language-py\">containers=[]\nclat = math.ceil(south*100)\nwhile clat &lt;= math.ceil(north*100):\n    clon = math.ceil(west*100)\n    while clon &lt;= math.ceil(east*100):\n        containers.append(\"geo_\"+re.sub('-','n', str(clat))+\"_\"+re.sub('-','n',str(clon)))\n        clon+=1\n    clat+=1\n<\/code><\/pre>\n<\/div>\n<p>\u30b3\u30f3\u30c6\u30ca\u306e\u30ea\u30b9\u30c8\u304c\u3067\u304d\u305f\u306e\u3067\u3001\u30d0\u30a6\u30f3\u30c7\u30a3\u30f3\u30b0\u30dc\u30c3\u30af\u30b9\u5185\u306e\u30dd\u30a4\u30f3\u30c8\u3092\u691c\u7d22\u3059\u308b\u30b7\u30f3\u30d7\u30eb\u306aTQL\u6587\u3067\u30b3\u30f3\u30c6\u30ca\u3092\u7167\u4f1a\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u308b\u3088\u3046\u306b\u306a\u308a\u307e\u3057\u305f\u3002<\/p>\n<div class=\"clipboard\">\n<pre><code class=\"language-py\">tql = \"select * where Latitude > %f and Latitude &lt; %f and Longitude &lt; %f and Longitude > %f\" %(south, north, east, west)\n\n\nfor container in containers:\n    ts = gridstore.get_container(container)\n    try:\n        query = ts.query(tql) \n        rs = query.fetch(False) \n\n        while rs.has_next():\n            complaints.append(rs.next()\n    except:\n        pass\n<\/code><\/pre>\n<\/div>\n<p>\u3053\u306e\u3088\u3046\u306a\u691c\u7d22\u3092\u5b9f\u884c\u3059\u308b\u969b\u306b\u306f\u3001\u30eb\u30fc\u30d7\u5185\u3067\u4f8b\u5916\u3092\u6355\u307e\u3048\u3066\u304a\u304f\u3053\u3068\u304c\u91cd\u8981\u3067\u3059\u3002\u6700\u521d\u306e\u30b3\u30f3\u30c6\u30ca\u306b\u306f\u7d50\u679c\u304c\u306a\u304b\u3063\u305f\u5834\u5408\u306b\u3001\u5f8c\u3067\u30af\u30a8\u30ea\u3055\u308c\u305f\u30b3\u30f3\u30c6\u30ca\u306b\u7d50\u679c\u304c\u3042\u308b\u306e\u306b\u3082\u95a2\u308f\u3089\u305a\u3001\u4f8b\u5916\u304c\u8fd4\u3063\u3066\u304d\u3066\u3057\u307e\u3046\u53ef\u80fd\u6027\u304c\u3042\u308b\u304b\u3089\u3067\u3059\u3002<\/p>\n<h2>\u307e\u3068\u3081<\/h2>\n<p>\u3053\u306e\u3088\u3046\u306b\u3001\u30d0\u30a6\u30f3\u30c7\u30a3\u30f3\u30b0\u30dc\u30c3\u30af\u30b9\u3092\u4f7f\u3046\u3068\u3001\u6307\u5b9a\u3057\u305f\u5834\u6240\u306e\u8fd1\u304f\u306b\u3042\u308b\u30c7\u30fc\u30bf\u3092\u7c21\u5358\u306b\u898b\u3064\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u3053\u306e\u30d6\u30ed\u30b0\u306e\u30bd\u30fc\u30b9\u30b3\u30fc\u30c9\u306f\u3001 <a href=\"https:\/\/github.com\/griddbnet\/\">GridDB.net GitHub<\/a>\u30ea\u30dd\u30b8\u30c8\u30ea\u3067\u516c\u958b\u3057\u3066\u3044\u307e\u3059\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u4ee5\u524d\u306e\u30cb\u30e5\u30fc\u30e8\u30fc\u30af\u306e\u72af\u7f6a\u306b\u95a2\u3059\u308b\u30d6\u30ed\u30b0\u3067\u306f\u3001GridDB\u306e\u30b8\u30aa\u30e1\u30c8\u30ea\uff08\u5e7e\u4f55\u5b66\uff09\u6a5f\u80fd\u3092\u4f7f\u3063\u305f\u5730\u7406\u7a7a\u9593\u30c7\u30fc\u30bf\u306e\u30af\u30a8\u30ea\u306b\u3064\u3044\u3066\u7d39\u4ecb\u3057\u307e\u3057\u305f\u3002 \u30b8\u30aa\u30e1\u30c8\u30ea\u3068WKT\uff08\u3088\u304f\u77e5\u3089\u308c\u3066\u3044\u308b\u5e7e\u4f55\u5b66\u306e\u30c6\u30ad\u30b9\u30c8\u8868\u73fe\uff09\u306e\u30af\u30a8\u30ea\u306f\u3046\u307e\u304f\u6a5f\u80fd\u3057\u307e\u3059 [&hellip;]<\/p>\n","protected":false},"author":71,"featured_media":50228,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[1005],"tags":[],"class_list":["post-50752","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-1005"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.1.1 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>\u30d0\u30a6\u30f3\u30c7\u30a3\u30f3\u30b0\u30dc\u30c3\u30af\u30b9\u3067\u5730\u7406\u7684\u30af\u30a8\u30ea\u3092\u4f7f\u3046 | GridDB: Open Source Time Series Database for IoT<\/title>\n<meta name=\"description\" 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